A computational approach to early sepsis detection

Computers in Biology and Medicine

Volumn 74, Issue , 2016, Pages 69-73

  Calvert, Jacob S ^a   Price, Daniel A ^a   Chettipally, Uli K ^b,c   Barton, Christopher W ^c   Feldman, Mitchell D ^c   Hoffman, Jana L ^a   Jay, Melissa ^a   Das, Ritankar ^a  

^a DASCENA INC   (United States)

^b KAISER PERMANENTE   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Clinical decision support systems; Computer assisted diagnosis; Early diagnosis; Medical informatics; Sepsis; Severe sepsis

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER AIDED DIAGNOSIS; DECISION SUPPORT SYSTEMS; FORECASTING; INFORMATION SCIENCE; INTENSIVE CARE UNITS; MEDICAL COMPUTING; RISK ASSESSMENT;

CLINICAL DECISION SUPPORT SYSTEMS; COMPUTER ASSISTED DIAGNOSIS; EARLY DIAGNOSIS; MEDICAL INFORMATICS; SEPSIS; SEVERE SEPSIS;

DIAGNOSIS;

BIOLOGICAL MARKER; PROCALCITONIN;

ADULT; ARTICLE; BLOOD OXYGEN TENSION; COEVOLUTION; COMPUTER ASSISTED DIAGNOSIS; EARLY DIAGNOSIS; GOLD STANDARD; HEART RATE; HOSPITAL ADMISSION; HOSPITALIZATION; HUMAN; INFORMED CONSENT; INTENSIVE CARE UNIT; MACHINE LEARNING; META ANALYSIS (TOPIC); PATIENT CODING; PREDICTIVE VALUE; PRIORITY JOURNAL; RETROSPECTIVE STUDY; RISK FACTOR; SENSITIVITY AND SPECIFICITY; SEPSIS; SYSTEMATIC REVIEW (TOPIC); SYSTOLIC BLOOD PRESSURE; TURNAROUND TIME; VITAL SIGN; FEMALE; INTENSIVE CARE; MALE; METABOLISM; PROCEDURES; TIME FACTOR;

ADULT; BIOMARKERS; CRITICAL CARE; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; MALE; RETROSPECTIVE STUDIES; SEPSIS; TIME FACTORS;

EID: 84969271438     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2016.05.003     Document Type: Article

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